Turnout Fault Diagnosis through Dynamic Time Warping and Signal Normalization

Abstract

Turnout is one key fundamental infrastructure in the railway signal system, which has great influence on the safety of railway systems. Currently, turnout fault diagnoses are conducted manually in China; engineers are obliged to observe the signals and make problem solving decisions. Thus, the accuracies of fault diagnoses totally depend on the engineers' experience although massive data are produced in real time by the turnout microcomputer-based monitoring systems. This paper aims to develop an intelligent diagnosis method for railway turnout through Dynamic Time Warping (DTW). We firstly extract the features of normal turnout operation current curve and normalize the collected turnout current curves. Then, five typical fault reference curves are ascertained through the microcomputer-based monitoring system, and DTW is used to identify the turnout current curve fault through test data. The analysis results based on the similarity data indicate that the analyzed five turnout fault types can be diagnosed automatically with 100% accuracy. Finally, the benefits of the proposed method and future research directions were discussed.

On the Fault Detection and Diagnosis of Railway Switch and Crossing Systems: An Overview

“…An FD technique only recognizes that a problem has occurred in the system, but it does not identify the root causes nor isolate the location of different faults (i.e., there is no isolation step). Thus, many researchers have developed different FDD techniques to deal with railway S&C system CM, and many papers can be found [11,13,15,28,34,[100][101][102][103][104][105][106][107][108][109][110][111][112][113][114][115][116][117]; only selected papers are discussed in the following. It should be clearly noted that the only criteria applied for this selection were that only the most recent published papers were chosen (from 2017 onwards).…”

“…In addition, a setup of laser-based non-contact 2D measurement of the crossing geometry has been considered to quantify the geometry change of the new crossing nose. With the aim of developing an intelligent FDD algorithm for railway S&C systems, a DTW method was proposed in [114]. Performance of the proposed data-driven FDD method was determined by analyzing the turnout current curves in healthy and five faulty cases: turnout suddenly stops running after starting, turnout jams, startup circuit disconnection, locking current exceeded, and automatic actuator is not flexible.…”

“…FDD methods [11,13,15,28,34,[100][101][102][103][104][105][106][107][108][109][110][111][112][113][114][115][116][117]120] PCA [102,117]; SVM [11,104,105,110]; SVM combined with other algorithms (e.g., PCA, envelope, etc.) [15,101,117]; wavelet transform (WT) and its variants (e.g., CWT and discrete WT (DWT)) [15,101]; DTW [111,112,114,115]; SOM [108]; backpropagation (BP) neural network (NN) [107]; probabilistic NN (PNN) [106]; 3D reconstruction [113]; k-nearest neighbor method [100]; fuzzy c-mean [116]; qualitative trend analysis (QTA) [13]; ANN [103]; BLT and NN…”

“…Voltage [15,100,101,104,108]; force [13,15,34,[100][101][102]120]; current [13,15,28,[100][101][102][103][105][106][107][108]110,111,[114][115][116][117]; power [11,34,117,120]; strain signal [110,113]; switch displacement [13]; linear position of the switch rails [104]; motor temperature [108]; audio signal (sound sensor) [117]; 2D measurements [113]; speed [120].…”

“…Wear in crossing [113]; switch-related faults [105][106][107][110][111][112]114,117]; slide chair-related faults [109,117]; startup circuit disconnection (bad contact) [106,107,114,115,117]; actuator is not flexible [114,115]; abnormal fluctuations [115]; electric relay switch failure [115]; mechanical jam fault [117]; abnormal impedance [117]; lack of motor lubrication [11]; overdriven and underdriven [13,15,34,101]; drive rod out of adjustment [104]; motor deblocking [107]; obstacles (hard or soft) [108,120]; left and right misaligned adjuster bolts [120]; missing bearings [120].…”